Research on Object Detection Technique in High Resolution Remote Sensing Images Based on U-Net

被引：0
作者：
Wu Zhihuan [1 ,2 ]
Gao Yongming [1 ]
Li Lei [1 ]
Fan Junliang [1 ]
机构：
[1] Space Engn Univ, Beijing 100416, Peoples R China
[2] 63883 Troops, Luoyang 471000, Peoples R China
来源：
PROCEEDINGS OF THE 30TH CHINESE CONTROL AND DECISION CONFERENCE (2018 CCDC) | 2018年
关键词：
object detection; remote Sensing; scene segmentation; convolutional neural networks;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Scene segmentation is an important method to implement fine-grained object detection in remote sensing image. The method based on fully convolution neural network is the hotspot in the field. In this paper, a hilly convolution neural network model based on U-Net model which achieves state of art result on biomedical segmentation application is proposed. Experiments on DSTL dataset show that the proposed model produces accurate pixel-wise classifications for remote sensing image in an end-to-end way.
引用
收藏
页码：2849 / 2853
页数：5
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